Umar Murtaza

DevOps & MLOps Engineer | Cloud Specialist (GCP, AWS, Azure)

DevOps and MLOps Engineer with 6+ years of remote experience designing and implementing cloud infrastructure across GCP, AWS, and Azure. Expert in building scalable web applications and AI/ML systems with comprehensive knowledge of 90+ cloud services. Proven track record delivering cost-optimized solutions for US and European clients while working fully remote since 2018.

Technical Skills

• Cloud Platforms: GCP (Expert), AWS (Expert), Azure (Proficient)
• Infrastructure as Code: Terraform, CloudFormation, Google Cloud Deployment Manager
• Containerization: Kubernetes (GKE, EKS, AKS), Docker, ECS, Cloud Run
• CI/CD & DevOps Tools: Jenkins, Google Cloud Build, AWS CodePipeline, Azure DevOps, Ansible
• Programming & Scripting: Python, Bash, YAML, HCL
• Operating Systems Administration: Linux (Ubuntu, Debian, CentOS), Solaris

Cloud Expertise

(a) GCP Services/Skills

• Compute & Containers: Compute Engine, GKE, Cloud Run, App Engine, Batch, Cloud Functions​
• AI/ML Platform: Vertex AI, Document AI, Gemini, Vision AI, Speech AI, NotebookLM​
• Data & Analytics: BigQuery, Dataflow, Pub/Sub, Dataproc, Composer, Looker​
• Storage & Databases: Cloud SQL (MySQL, PostgreSQL), Firestore, Bigtable, Memorystore, Cloud Storage, Filestore​
• Networking: VPC, Load Balancing, Cloud CDN, Cloud DNS, Cloud NAT, Interconnect, VPN​
• DevOps & CI/CD: Cloud Build, Artifact Registry, Container Registry, Cloud Deploy, Source Repositories​
• Serverless & Integration: Cloud Functions, Cloud Scheduler, Cloud Tasks, Workflows, API Gateway, Apigee​
• Observability: Cloud Monitoring, Logging, Trace, Error Reporting​
• Security & Management: IAM, Organizations, Security Command Center, Deployment Manager

(b) AWS Services/Skills

• Compute & Containers: EC2, ECS, EKS, Lambda, Batch, Elastic Beanstalk, Lightsail​
• AI/ML Service: SageMaker, Polly, Rekognition​
• Storage & Databases: S3, EFS, RDS, DynamoDB, ElastiCache, DocumentDB, MemoryDB, AWS Backup
• Networking & CDN: VPC, CloudFront, API Gateway, Route 53, WAF & Shield
• DevOps & Developer Tools: CodePipeline, CodeBuild, CodeDeploy, CodeCommit, CodeArtifact
• Management/Governance: CloudWatch, CloudFormation, CloudTrail, AWS Config, Organizations, Trusted Advisor
• Security & Compliance: IAM, KMS, Certificate Manager, Secrets Manager
• Application Integration: SQS, SNS, Step Functions, Amazon MQ, SES
• IoT & Edge: IoT Core, IoT Events
• Cost Management: Billing Conductor, Cost Explorer

(c) Azure Services/Skills

• Compute & Containers: Virtual Machines, AKS, Azure Container Registry, Container Storage
• Databases: Azure SQL, Azure Cache for Redis
• DevOps: Azure DevOps
• Networking: Azure Firewall, NAT Gateway, Load Balancer, Virtual Network
• Storage: Blob Storage, Disk Storage, Container Storage, Storage Accounts

Cloud Certifications

• Google Professional Cloud Architect by Google Cloud Platform (GCP)
• Amazon Web Services Solutions Architect Associate by Amazon Web Services (AWS)

Professional Affiliations

• Member | AI Accelerator Institute | May 2023 - Present​
• Connecting and empowering AI infrastructure innovators
• AWS Community Builder | Amazon Web Services | May 2021 - May 2023​
• Built AWS Community through meetups, training, and live sessions

Additional Courses

DevOps Courses (from LinuxAcademy)

• DevOps Essentials
• Docker Quick Start / Docker Deep Dive
• Using Ansible for CM and Deployments
• Jenkins Quick Start / Jenkins and Build Automation
• Container Clusters with Kubernetes
• Puppet Quick Start
• Learning Vagrant
• Ansible Quick Start

Machine Learning Courses (From Coursera)

• Machine Learning with TensorFlow on GCP
• How Google does Machine Learning
• Art and Science of Machine Learning - Feature Engineering
• Intro to TensorFlow
• Launching into Machine Learning

Data Science Courses (From DataCamp)

• Cleaning Data in Python
• Data Manipulation
• Data Scientist with Python
• Importing & Cleaning Data with Python
• Importing Data in Python (Part 1 & 2)
• Intermediate Python for Data Science
• Intro to Python for Data Science
• Introduction to Databases in Python
• Machine Learning with Python
• Python Data Science Toolbox

Some Recent Projects and Technologies

• Deployment and Maintenance of GKE Clusters in Development, Staging and Production Environments
• Scripting deployment of a complete Project with GKE in GCP
• Scripting/Terraforming deployment of a complete infrastructure in AWS
• Terraforming App Engine, Cloud SQL, MongoDB, VMs and MemoryStore in GCP
• Migration to Google Cloud Platform, with web application, databases and storage
• Setting up number of GKE clusters for clients for online services
• Setup of multiple projects for DICOM services for a US client
• Setup of ML Based services infrastructure using GKE (with GPUs) and VMs